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Optimization algorithm applied to extended range fuel cell hybrid vehicles. Contribution to road transport decarbonization

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  • Perez-Dávila, Oriana
  • Álvarez Fernández, Roberto

Abstract

Progressive decarbonization of road transport is underway to reduce greenhouse gas (GHG) emissions and their harmful effects. Although different options have already been considered, hydrogen-electric hybridization seems to be an interesting option to reduce emissions by offering vehicles with sufficient range and competitive performance compared to fossil fuel vehicles. The development of energy management systems (EMS) that achieve efficient use of energy is crucial to extend the vehicles range. In this paper we propose two energy management systems applied to two hydrogen hybrid vehicles: a Plug-in Hybrid Electric Vehicle (PHEV) and a Range-Extended Fuel Cell Hybrid Vehicle (FC-EREV). The proposed EMSs are based on single and multi-level approaches, that consider the amount of hydrogen in the tank to implement a rule-based strategy (RBS) that distributes the current demanded by the motor between the fuel cell and the battery. The EMS parameters for both approaches were selected using a particle swarm optimization (PSO) algorithm in order to find the optimized set of values for both EMS. The proposals have been tested for different driving cycles, showing improvements up to 9% and 12% in range, for the single and multi-level approaches, respectively, when compared to previous works.

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  • Perez-Dávila, Oriana & Álvarez Fernández, Roberto, 2023. "Optimization algorithm applied to extended range fuel cell hybrid vehicles. Contribution to road transport decarbonization," Energy, Elsevier, vol. 267(C).
    • Handle: RePEc:eee:energy:v:267:y:2023:i:c:s0360544222034053
    DOI: 10.1016/j.energy.2022.126519
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    References listed on IDEAS

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    1. Sulaiman, N. & Hannan, M.A. & Mohamed, A. & Ker, P.J. & Majlan, E.H. & Wan Daud, W.R., 2018. "Optimization of energy management system for fuel-cell hybrid electric vehicles: Issues and recommendations," Applied Energy, Elsevier, vol. 228(C), pages 2061-2079.
    2. Mahmoodi-k, Mehdi & Montazeri, Morteza & Madanipour, Vahid, 2021. "Simultaneous multi-objective optimization of a PHEV power management system and component sizing in real world traffic condition," Energy, Elsevier, vol. 233(C).
    3. Samsatli, Sheila & Samsatli, Nouri J., 2019. "The role of renewable hydrogen and inter-seasonal storage in decarbonising heat – Comprehensive optimisation of future renewable energy value chains," Applied Energy, Elsevier, vol. 233, pages 854-893.
    4. Weiss, Martin & Patel, Martin K. & Junginger, Martin & Perujo, Adolfo & Bonnel, Pierre & van Grootveld, Geert, 2012. "On the electrification of road transport - Learning rates and price forecasts for hybrid-electric and battery-electric vehicles," Energy Policy, Elsevier, vol. 48(C), pages 374-393.
    5. Zhou, Yang & Ravey, Alexandre & Péra, Marie-Cecile, 2020. "Multi-mode predictive energy management for fuel cell hybrid electric vehicles using Markov driving pattern recognizer," Applied Energy, Elsevier, vol. 258(C).
    6. Molina, S. & Novella, R. & Pla, B. & Lopez-Juarez, M., 2021. "Optimization and sizing of a fuel cell range extender vehicle for passenger car applications in driving cycle conditions," Applied Energy, Elsevier, vol. 285(C).
    7. Fuad Un-Noor & Sanjeevikumar Padmanaban & Lucian Mihet-Popa & Mohammad Nurunnabi Mollah & Eklas Hossain, 2017. "A Comprehensive Study of Key Electric Vehicle (EV) Components, Technologies, Challenges, Impacts, and Future Direction of Development," Energies, MDPI, vol. 10(8), pages 1-84, August.
    8. Fathy, Ahmed & Rezk, Hegazy & Nassef, Ahmed M., 2019. "Robust hydrogen-consumption-minimization strategy based salp swarm algorithm for energy management of fuel cell/supercapacitor/batteries in highly fluctuated load condition," Renewable Energy, Elsevier, vol. 139(C), pages 147-160.
    9. Sharaf, Omar Z. & Orhan, Mehmet F., 2014. "An overview of fuel cell technology: Fundamentals and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 810-853.
    10. Brand, Christian & Cluzel, Celine & Anable, Jillian, 2017. "Modeling the uptake of plug-in vehicles in a heterogeneous car market using a consumer segmentation approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 121-136.
    11. Álvarez Fernández, Roberto & Corbera Caraballo, Sergio & Beltrán Cilleruelo, Fernando & Lozano, J. Antonio, 2018. "Fuel optimization strategy for hydrogen fuel cell range extender vehicles applying genetic algorithms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 655-668.
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    1. Zhou, Hongxu & Yu, Zhongwei & Wu, Xiaohua & Fan, Zhanfeng & Yin, Xiaofeng & Zhou, Lingxue, 2023. "Dynamic programming improved online fuzzy power distribution in a demonstration fuel cell hybrid bus," Energy, Elsevier, vol. 284(C).

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